At a Glance
- Tasks: Develop AI-powered solutions and enhance our retrieval-augmented generation platform.
- Company: Join Zendesk, a leader in customer experience technology.
- Benefits: Flexible hours, professional development funds, and a remote-friendly environment.
- Other info: Collaborative team culture with opportunities for growth and specialisation.
- Why this job: Make a real impact on millions of customers with cutting-edge AI technology.
- Qualifications: 4+ years in machine learning, Python expertise, and cloud service management.
The predicted salary is between 70000 - 90000 £ per year.
About the Role
Zendesk's people have one goal in mind: to make Customer Experience better. Our products help more than 125,000 global brands (AirBnb, Uber, JetBrains, Slack, among others) make their billions of customers happy, every day. Our team is dedicated to providing a state-of-the-art retrieval-augmented generation (RAG) platform across multiple channels, including customer service bots, email, and search. In collaboration with ML scientists, we deliver high-quality AI products leveraging the latest tools and techniques, and serve them at a scale that most companies can only dream of. We’re passionate about empowering end-users to quickly find answers to their questions and helping our customers make the most of their knowledge base.
What you’ll be doing:
- Delivering AI-powered capabilities to our customers at Zendesk scale using the latest in LLM technology.
- Working closely with Product Management, ML Scientists, and other ML Engineers to define feature scope and implementation strategies.
- Mentoring junior team members, as well as pairing with more experienced colleagues to foster mutual learning.
- Supporting our deployed services to ensure a high level of stability and reliability.
- Contributing to discussions regarding technical design and best practices.
- Writing clean and maintainable code to meet the team’s delivery commitments.
Here are some of the challenges you will be working on:
- How do we best expand our RAG platform to handle new use cases?
- How do we optimize our system for both speed and cost-efficiency?
- How do we incorporate multiple sources of context to improve the accuracy of our generated answers?
- How do we make the best use of rapidly evolving LLM technologies?
What you bring to the role:
Basic Qualifications:
- 4+ years developing machine learning systems in Python.
- Solid understanding of architecture and software design patterns for server-side applications.
- Experience with managing and deploying cloud services with a cloud provider (AWS, GCP, Azure).
- Experience building scalable and stable software applications.
- Collaborative and growth mindset, with a commitment to ongoing learning and development.
- Self-managed and agile, with the ability to problem-solve independently.
- Excellent communication skills, both written and verbal.
Preferred Qualifications:
- Experience with using LLMs at scale.
- Experience in designing and implementing RAG systems.
- Experience with managing and deploying cloud services with AWS.
- Proven experience making data-driven engineering decisions; formulating hypotheses, conducting experiments, and analyzing results.
What our tech stack looks like:
Our code is largely written in Python, with some parts in Ruby. Our platform is built on AWS. Data is stored in RDS MySQL, Redis, S3, ElasticSearch, Kafka, and Athena. Services are deployed to Kubernetes using Docker, with Kafka for stream processing. Infrastructure health is monitored using Datadog and Sentry.
What we offer:
- Team of passionate people who love what they do!
- Exciting opportunity to work with LLMs and RAG (retrieval augmented generation), rapidly evolving fields in AI.
- Ownership of the product features at scale, making a significant impact for millions of customers.
- Opportunity to learn and grow!
- Possibility to specialise in areas such as security, performance, and reliability.
- Flexible working hours.
- Professional development funds.
- Comfortable office and a remote-friendly environment.
Senior Machine Learning Engineer employer: Zendesk
Zendesk is an exceptional employer, offering a dynamic work culture where innovation thrives and employees are empowered to make a real impact on customer experience for over 125,000 global brands. With a strong focus on professional development, flexible working hours, and the opportunity to work with cutting-edge technologies in AI, employees can expect meaningful growth and collaboration in a supportive environment that values both individual contributions and team success.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Zendesk or similar companies. Use LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially any that involve LLMs or RAG systems. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past experiences in detail, especially around cloud services and scalable applications.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our awesome team at Zendesk!
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with Python, cloud services, and any relevant projects that showcase your skills in LLMs and RAG systems.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about improving customer experience through AI and how your background aligns with our mission at Zendesk.
Showcase Your Problem-Solving Skills:In your application, don’t forget to mention specific challenges you've tackled in previous roles. We love seeing how you approach problem-solving, especially in machine learning contexts!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our team!
How to prepare for a job interview at Zendesk
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially Python, AWS, and Kubernetes. Be ready to discuss how you've used these tools in your previous roles and how they can be applied to enhance Zendesk's RAG platform.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in machine learning projects. Think about how you approached these problems, the solutions you implemented, and the outcomes. This will demonstrate your ability to tackle the complex issues Zendesk is dealing with.
✨Emphasise Collaboration
Since the role involves working closely with Product Management and ML Scientists, highlight your experience in collaborative environments. Share examples of how you've mentored others or worked in teams to achieve common goals, showcasing your growth mindset.
✨Prepare for Technical Discussions
Be ready to dive into technical design and best practices during the interview. Brush up on software design patterns and be prepared to discuss how you ensure code quality and maintainability in your projects. This will show that you’re not just a coder but a thoughtful engineer.
